The background description provided herein is for the purpose of generally presenting the context of the disclosure. Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
Trained feature detection algorithms are known and used to detect people; examples include Haar-like feature identification, histogram of oriented gradients (“HOG”) descriptors, scale-invariant feature transform (“SIFT”) identification, and speeded-up robust feature (“SURF”) detection. However, such algorithms require training, may be computationally expensive, and have difficulty compensating for overlaps in the object that they trained to identify. Overhead cameras are also used to detect people, though these cannot detect whether a human is interested in specific shelf or product thereon.